Detection of Mycobacterium Tuberculosis Using Residual Neural Network
Author:
Affiliation:
1. Institut Teknologi Bandung,School of Electrical Engineering and Informatics,Bandung,Indonesia
2. Andalas University,Department of Electrical Engineering,Padang,Indonesia
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9855197/9855201/09855300.pdf?arnumber=9855300
Reference18 articles.
1. Artificial Intelligence–Based Screening for Mycobacteria in Whole-Slide Images of Tissue Samples
2. Automatic detection of mycobacterium tuberculosis using artificial intelligence
3. A CNN-based active learning framework to identify mycobacteria in digitized Ziehl-Neelsen stained human tissues
4. Computer-Aided Bacillus Detection in Whole-Slide Pathological Images Using a Deep Convolutional Neural Network
5. Automatic Bacillus Detection in Light Field Microscopy Images Using Convolutional Neural Networks and Mosaic Imaging Approach
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1. Influence of Adam Optimizer with Sequential Convolutional Model for Detection of Tuberculosis;2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO);2022-12
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